Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting

We consider the problem of sampling from a high-dimensional target distribution πβ on Rd with density proportional to θ↦e−βU(θ) using explicit numerical schemes based on discretising the Langevin stochastic differential equation (SDE). In recent literature, taming has been proposed and studied as a...

全面介紹

Saved in:
書目詳細資料
Main Authors: Neufeld, Ariel, Ng, Matthew Cheng En, Zhang, Ying
其他作者: School of Physical and Mathematical Sciences
格式: Article
語言:English
出版: 2025
主題:
在線閱讀:https://hdl.handle.net/10356/182195
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Nanyang Technological University
語言: English

相似書籍